AI evals are becoming the new compute bottleneck
AI model evaluations are becoming a significant computational bottleneck, demanding more resources than model training.
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Together AI announces a new feature allowing users to fine-tune any LLM from the Hugging Face Hub.
Why it matters
This development is significant because it lowers the barrier to entry for customizing large language models. By integrating with the Hugging Face Hub, Together AI provides access to a vast library of pre-trained models, enabling developers and researchers to tailor these powerful AI tools to specific tasks and datasets without requiring extensive infrastructure or deep expertise in model training. This democratization of LLM fine-tuning can accelerate innovation across various AI applications.
Together AI now lets you easily customize any AI language model found on Hugging Face. This makes it simpler for anyone to build specialized AI tools for their needs.
AI model evaluations are becoming a significant computational bottleneck, demanding more resources than model training.
Read on Hugging Face Blog →Yotta and Gorilla Technology are expanding their AI infrastructure partnership in India with a $2.8 billion project to deploy an additional 20,736 GPU cards by September 2026, significantly boosting the country's AI compute capabilities.
Read on Economic Times Tech →Hugging Face integrates DeepInfra as an inference provider, allowing users to deploy models more efficiently.
Read on Hugging Face Blog →